空中交通管制专家与新手眼动行为的统计分析研究

Statistical Analysis of Eye Movements between Air Traffic Control Experts and Novices

数据科学的迅速发展促进了心理学、管理学等各学科研究范式的转变。通过对实证数据的深入研究,能够发现传统方法不能发现的规律。该文以管制员眼动行为为研究对象,通过face LAB眼动仪采集不同级别管制员的眼动行为数据,综合统计分析方法和MF-DFA时间序列分析方法对数据进行了深入分析,探讨不同级别管制员在信息获取行为上的差异。分析结果表明:1)专家比新手具有更长的平均注视持续时间、更少的注视点、更少的平均扫视持续时间和更小的扫视幅度;2)管制员的注视持续时间、扫视持续时间和扫视幅度的时间序列有多重分形特征,多重分形奇异谱图表明新手的波动强度大于专家。研究结果说明管制员的信息获取行为具有差异性,管制经验对管制员行为特征具有显著影响。

The advancement of data science has been prompting the shift of research paradigms in various fields, including psychology, management etc.Investigations on the large empirical datasets have uncovered astonishing regularities and universalities which cannot be revealed through classic methods. This paper aims to explore the fundamental differences in air traffic controllers＇ information seeking behavior based on the analysis of their eye movements＇ data. The faceLAB is used to collect eye movements＇ data recorded from 14 air traffic controllers. Statistical analysis and multifractal detrended fluctuation analysis （MF-DFA） are carried out to investigate the fundamental properties of eye movements. The analytical results show that 1） expert controllers have longer mean fixation duration, less fixation points, shorter mean saccadic duration, and smaller mean saccadic velocity than novices; 2） Controllers＇ fixation time series, saccadic duration time series, and saccadic amplitude time series, allexhibit multifractal characteristics, and multifractal singularity spectrum demonstrates that there are stronger fluctuations in novices＇ fixation activities. Our workindicates thatcontroller＇s information seeking dynamics are different.Work experience does have a significant impact on controllers＇ behavior.